Machine Learning and Data Analytics for Solving Business Problems Machine Learning and Data Analytics for Solving Business Problems
Unsupervised and Semi-Supervised Learning

Machine Learning and Data Analytics for Solving Business Problems

Methods, Applications, and Case Studies

Bader Alyoubi والمزيد
    • ‏139٫99 US$
    • ‏139٫99 US$

وصف الناشر

This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making processes. These methods form the theoretical foundations of intelligent management systems, which allows for companies to understand the market environment, to improve the analysis of customer needs, to propose creative personalization of contents, and to design more effective business strategies, products, and services. This book gives an overview of recent methods – such as blockchain, big data, artificial intelligence, and cloud computing – so readers can rapidly explore them and their applications to solve common business challenges. The book aims to empower readers to leverage and develop creative supervised and unsupervised methods to solve business decision-making problems.Provides design and applications of machine learning and data analytics to solve business problems; Includes applications of supervised and unsupervised learning methods in intelligent management systems; Introduces case studies of business problems solved using innovative learning methods and data analytics techniques.

النوع
تخصصات مهنية وتقنية
تاريخ النشر
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١٥ ديسمبر
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer International Publishing
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Super-Resolution for Remote Sensing Super-Resolution for Remote Sensing
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Unsupervised Feature Extraction Applied to Bioinformatics Unsupervised Feature Extraction Applied to Bioinformatics
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Advances in Computational Logistics and Supply Chain Analytics Advances in Computational Logistics and Supply Chain Analytics
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Feature and Dimensionality Reduction for Clustering with Deep Learning Feature and Dimensionality Reduction for Clustering with Deep Learning
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Hidden Markov Models and Applications Hidden Markov Models and Applications
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Partitional Clustering via Nonsmooth Optimization Partitional Clustering via Nonsmooth Optimization
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